3 research outputs found
A Computational QSAR, Molecular Docking and In Vitro Cytotoxicity Study of Novel Thiouracil-Based Drugs with Anticancer Activity against Human-DNA Topoisomerase II
Computational chemistry, molecular docking, and drug design approaches, combined with the biochemical evaluation of the antitumor activity of selected derivatives of the thiouracil-based dihydroindeno pyrido pyrimidines against topoisomerase I and II. The IC50 of other cell lines including the normal human lung cell line W138, lung cancer cell line, A549, breast cancer cell line, MCF-7, cervical cancer, HeLa, and liver cancer cell line HepG2 was evaluated using biochemical methods. The global reactivity descriptors and physicochemical parameters were computed, showing good agreement with the Lipinski and Veber’s rules of the drug criteria. The molecular docking study of the ligands with the topoisomerase protein provides the binding sites, binding energies, and deactivation constant for the inhibition pocket. Various biochemical methods were used to evaluate the IC50 of the cell lines. The QSAR model was developed for colorectal cell line HCT as a case study. Four QSAR statistical models were predicted between the IC50 of the colorectal cell line HCT to correlate the anticancer activity and the computed physicochemical and quantum chemical global reactivity descriptors. The predictive power of the models indicates a good correlation between the observed and the predicted activity
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DFT and molecular simulation validation of the binding activity of PDEδ inhibitors for repression of oncogenic k-Ras.
The development of effective drugs targeting the K-Ras oncogene product is a significant focus in anticancer drug development. Despite the lack of successful Ras signaling inhibitors, recent research has identified PDEδ, a KRAS transporter, as a potential target for inhibiting the oncogenic KRAS signaling pathway. This study aims to investigate the interactions between eight K-Ras inhibitors (deltarazine, deltaflexin 1 and 2, and its analogues) and PDEδ to understand their binding modes. The research will utilize computational techniques such as density functional theory (DFT) and molecular electrostatic surface potential (MESP), molecular docking, binding site analyses, molecular dynamic (MD) simulations, electronic structure computations, and predictions of the binding free energy. Molecular dynamic simulations (MD) will be used to predict the binding conformations and pharmacophoric features in the active site of PDEδ for the examined structures. The binding free energies determined using the MMPB(GB)SA method will be compared with the observed potency values of the tested compounds. This computational approach aims to enhance understanding of the PDEδ selective mechanism, which could contribute to the development of novel selective inhibitors for K-Ras signaling